{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"http://hilpisch.com/tpq_logo.png\" alt=\"The Python Quants\" width=\"35%\" align=\"right\" border=\"0\"><br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Python for Finance (2nd ed.)\n",
    "\n",
    "**Mastering Data-Driven Finance**\n",
    "\n",
    "&copy; Dr. Yves J. Hilpisch | The Python Quants GmbH\n",
    "\n",
    "<img src=\"http://hilpisch.com/images/py4fi_2nd_shadow.png\" width=\"300px\" align=\"left\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Input-Output Operations"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Basic I/O with Python"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Writing Objects to Disk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pylab import plt, mpl\n",
    "plt.style.use('seaborn-v0_8')\n",
    "mpl.rcParams['font.family'] = 'serif'\n",
    "# %config InlineBackend.figure_format = 'svg'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "uuid": "c2722e94-01ea-4f98-804f-56fe1b666770"
   },
   "outputs": [],
   "source": [
    "import pickle  \n",
    "import numpy as np\n",
    "from random import gauss   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "uuid": "7d03b06c-a907-4a16-913f-e6a8f9a05d51"
   },
   "outputs": [],
   "source": [
    "a = [gauss(1.5, 2) for i in range(1000000)]  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "uuid": "d5bf9798-386b-49b8-a703-36263d9d75d4"
   },
   "outputs": [],
   "source": [
    "# adjust to path of your choice\n",
    "path = '/Users/yves/Temp/data/'  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "uuid": "4aa88b7c-3155-4311-9afc-564bf3b06225"
   },
   "outputs": [],
   "source": [
    "pkl_file = open(path + 'data.pkl', 'wb')  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "uuid": "e2611db7-97ed-4162-9cc5-127c7cd89cbd"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 9.13 ms, sys: 4.14 ms, total: 13.3 ms\n",
      "Wall time: 12.5 ms\n"
     ]
    }
   ],
   "source": [
    "%time pickle.dump(a, pkl_file)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "uuid": "f2b0c608-c399-401b-b8fa-d44d8eca54b8"
   },
   "outputs": [],
   "source": [
    "pkl_file.close()  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "uuid": "f401db99-56f3-49a5-9c75-772fe5d00d07"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-rw-r--r--  1 yves  staff  9003247 Oct 15 08:34 /Users/yves/Temp/data/data.pkl\n"
     ]
    }
   ],
   "source": [
    "ll $path*  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "uuid": "8c9bd301-e980-4eb5-9021-4fde182f5eb7"
   },
   "outputs": [],
   "source": [
    "pkl_file = open(path + 'data.pkl', 'rb')  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "uuid": "6c8c4ae7-1ece-4b7c-87bc-8457da4798b2"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 11.9 ms, sys: 11 ms, total: 22.8 ms\n",
      "Wall time: 22.4 ms\n"
     ]
    }
   ],
   "source": [
    "%time b = pickle.load(pkl_file)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "uuid": "253951a8-ecec-4fdf-a502-86cfa1d1186d"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0.9358514495824233, 2.038581760919787, 1.2975214926013932]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "uuid": "8bf2e00b-fa06-4524-aa51-6b295fabad00"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0.9358514495824233, 2.038581760919787, 1.2975214926013932]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b[:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "uuid": "90b9f136-8195-4f32-9907-1b88469ae55e"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.allclose(np.array(a), np.array(b))  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "uuid": "7a6b9460-b5ac-4ab5-b083-9912f9dfcef8"
   },
   "outputs": [],
   "source": [
    "pkl_file = open(path + 'data.pkl', 'wb')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "uuid": "bd6b8e9a-d093-4f98-b88c-27aef388957b"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 32.5 ms, sys: 3.62 ms, total: 36.1 ms\n",
      "Wall time: 35.4 ms\n"
     ]
    }
   ],
   "source": [
    "%time pickle.dump(np.array(a), pkl_file)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "uuid": "d517f9d6-8176-424c-89ef-0c892f9fd61c"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 33.4 ms, sys: 4.35 ms, total: 37.8 ms\n",
      "Wall time: 37.2 ms\n"
     ]
    }
   ],
   "source": [
    "%time pickle.dump(np.array(a) ** 2, pkl_file)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "uuid": "5f558934-6f53-472e-9040-a5c96ee1718d"
   },
   "outputs": [],
   "source": [
    "pkl_file.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "uuid": "b129b0ae-6bcc-4946-817a-ff01c155eacb"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-rw-r--r--  1 yves  staff  16000324 Oct 15 08:34 /Users/yves/Temp/data/data.pkl\n"
     ]
    }
   ],
   "source": [
    "ll $path*  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "uuid": "59d5dceb-8779-46ff-b2ae-c2e43a7d2c10"
   },
   "outputs": [],
   "source": [
    "pkl_file = open(path + 'data.pkl', 'rb')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "uuid": "0f981d7b-0a68-412d-bb9b-a377524e0f2c"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.93585145, 2.03858176, 1.29752149, 3.1928892 ])"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = pickle.load(pkl_file)  \n",
    "x[:4]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "uuid": "1a9cb2b5-a180-43f3-b2ed-20de3148b8a6"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.87581794,  4.1558156 ,  1.68356202, 10.19454144])"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y = pickle.load(pkl_file)  \n",
    "y[:4]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "uuid": "6beb0285-c53c-4f56-ac42-62000ef75257"
   },
   "outputs": [],
   "source": [
    "pkl_file.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "uuid": "df469b3f-55c4-43e8-a01d-f850f2153871"
   },
   "outputs": [],
   "source": [
    "pkl_file = open(path + 'data.pkl', 'wb')\n",
    "pickle.dump({'x': x, 'y': y}, pkl_file)  \n",
    "pkl_file.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "uuid": "e6f0219a-ceb4-481d-b033-065e122493c8"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "x [0.93585145 2.03858176 1.29752149 3.1928892 ]\n",
      "y [ 0.87581794  4.1558156   1.68356202 10.19454144]\n"
     ]
    }
   ],
   "source": [
    "pkl_file = open(path + 'data.pkl', 'rb')\n",
    "data = pickle.load(pkl_file)  \n",
    "pkl_file.close()\n",
    "for key in data.keys():\n",
    "    print(key, data[key][:4])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "uuid": "dc3181d1-7c8c-4960-8a9a-8a4d64c58a3f"
   },
   "outputs": [],
   "source": [
    "!rm -f $path*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Reading and Writing Text Files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "uuid": "5124219c-e041-4b36-af62-03faea5c0df1"
   },
   "outputs": [],
   "source": [
    "rows = 5000  \n",
    "a = np.random.standard_normal((rows, 5)).round(4)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "uuid": "5942c6e2-877a-4c0c-acca-11390e9a02f5"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-0.7159,  0.3038,  0.4157,  0.1359,  3.1068],\n",
       "       [-0.3781,  1.0455, -0.7928, -0.5391,  1.0638],\n",
       "       [ 1.0701,  0.7203,  0.3972, -0.0993,  1.1648],\n",
       "       ...,\n",
       "       [-0.3489,  0.2703, -0.4961, -1.8348,  0.6701],\n",
       "       [ 0.3618,  1.6229, -1.5897, -1.9453, -0.7311],\n",
       "       [-0.2626,  0.3815, -0.3234, -0.0841, -0.2811]])"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "uuid": "32f5b082-2fcb-4090-80ba-174cc347e519"
   },
   "outputs": [],
   "source": [
    "t = pd.date_range(start='2019/1/1', periods=rows, freq='H')  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "uuid": "d52b1a47-3bca-4870-9829-1aef62f0952a"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2019-01-01 00:00:00', '2019-01-01 01:00:00',\n",
       "               '2019-01-01 02:00:00', '2019-01-01 03:00:00',\n",
       "               '2019-01-01 04:00:00', '2019-01-01 05:00:00',\n",
       "               '2019-01-01 06:00:00', '2019-01-01 07:00:00',\n",
       "               '2019-01-01 08:00:00', '2019-01-01 09:00:00',\n",
       "               ...\n",
       "               '2019-07-27 22:00:00', '2019-07-27 23:00:00',\n",
       "               '2019-07-28 00:00:00', '2019-07-28 01:00:00',\n",
       "               '2019-07-28 02:00:00', '2019-07-28 03:00:00',\n",
       "               '2019-07-28 04:00:00', '2019-07-28 05:00:00',\n",
       "               '2019-07-28 06:00:00', '2019-07-28 07:00:00'],\n",
       "              dtype='datetime64[ns]', length=5000, freq='H')"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "uuid": "39075f54-64cb-42c2-9798-be6638636a15"
   },
   "outputs": [],
   "source": [
    "csv_file = open(path + 'data.csv', 'w')  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "uuid": "3804898d-dae7-4de0-b0a1-976cd8e43cb3"
   },
   "outputs": [],
   "source": [
    "header = 'date,no1,no2,no3,no4,no5\\n'  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "uuid": "3804898d-dae7-4de0-b0a1-976cd8e43cb3"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "25"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "csv_file.write(header)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "uuid": "00c96e45-bf91-42d8-b6c9-eb343ee537b7"
   },
   "outputs": [],
   "source": [
    "for t_, (no1, no2, no3, no4, no5) in zip(t, a):  \n",
    "    s = '{},{},{},{},{},{}\\n'.format(t_, no1, no2, no3, no4, no5)  \n",
    "    csv_file.write(s)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "uuid": "00c96e45-bf91-42d8-b6c9-eb343ee537b7"
   },
   "outputs": [],
   "source": [
    "csv_file.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "uuid": "03523876-01c1-410f-aac5-55fcf8aa0604"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-rw-r--r--  1 yves  staff  284693 Oct 15 08:34 /Users/yves/Temp/data/data.csv\n"
     ]
    }
   ],
   "source": [
    "ll $path*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "uuid": "b290e5d3-8e56-4d53-acae-51accd08c4f7"
   },
   "outputs": [],
   "source": [
    "csv_file = open(path + 'data.csv', 'r')  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "uuid": "7b1242f5-5892-44bd-a305-addf9daff316"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "date,no1,no2,no3,no4,no5\n",
      "2019-01-01 00:00:00,-0.7159,0.3038,0.4157,0.1359,3.1068\n",
      "2019-01-01 01:00:00,-0.3781,1.0455,-0.7928,-0.5391,1.0638\n",
      "2019-01-01 02:00:00,1.0701,0.7203,0.3972,-0.0993,1.1648\n",
      "2019-01-01 03:00:00,-1.086,1.122,-0.1874,0.1372,-1.3463\n"
     ]
    }
   ],
   "source": [
    "for i in range(5):\n",
    "    print(csv_file.readline(), end='')  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "uuid": "2b2384ca-8927-49e1-8070-33ef0c21a1a9"
   },
   "outputs": [],
   "source": [
    "csv_file.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "uuid": "00148061-9d3a-4459-b8b8-63c98f14194b"
   },
   "outputs": [],
   "source": [
    "csv_file = open(path + 'data.csv', 'r')  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "uuid": "00148061-9d3a-4459-b8b8-63c98f14194b"
   },
   "outputs": [],
   "source": [
    "content = csv_file.readlines()  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['date,no1,no2,no3,no4,no5\\n',\n",
       " '2019-01-01 00:00:00,-0.7159,0.3038,0.4157,0.1359,3.1068\\n',\n",
       " '2019-01-01 01:00:00,-0.3781,1.0455,-0.7928,-0.5391,1.0638\\n',\n",
       " '2019-01-01 02:00:00,1.0701,0.7203,0.3972,-0.0993,1.1648\\n',\n",
       " '2019-01-01 03:00:00,-1.086,1.122,-0.1874,0.1372,-1.3463\\n']"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "content[:5]  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "uuid": "2b2384ca-8927-49e1-8070-33ef0c21a1a9"
   },
   "outputs": [],
   "source": [
    "csv_file.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "uuid": "2b2384ca-8927-49e1-8070-33ef0c21a1a9"
   },
   "outputs": [],
   "source": [
    "import csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(path + 'data.csv', 'r') as f:\n",
    "    csv_reader = csv.reader(f)  \n",
    "    lines = [line for line in csv_reader]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[['date', 'no1', 'no2', 'no3', 'no4', 'no5'],\n",
       " ['2019-01-01 00:00:00', '-0.7159', '0.3038', '0.4157', '0.1359', '3.1068'],\n",
       " ['2019-01-01 01:00:00', '-0.3781', '1.0455', '-0.7928', '-0.5391', '1.0638'],\n",
       " ['2019-01-01 02:00:00', '1.0701', '0.7203', '0.3972', '-0.0993', '1.1648'],\n",
       " ['2019-01-01 03:00:00', '-1.086', '1.122', '-0.1874', '0.1372', '-1.3463']]"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lines[:5]  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(path + 'data.csv', 'r') as f:\n",
    "    csv_reader = csv.DictReader(f)  \n",
    "    lines = [line for line in csv_reader]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'date': '2019-01-01 00:00:00',\n",
       "  'no1': '-0.7159',\n",
       "  'no2': '0.3038',\n",
       "  'no3': '0.4157',\n",
       "  'no4': '0.1359',\n",
       "  'no5': '3.1068'},\n",
       " {'date': '2019-01-01 01:00:00',\n",
       "  'no1': '-0.3781',\n",
       "  'no2': '1.0455',\n",
       "  'no3': '-0.7928',\n",
       "  'no4': '-0.5391',\n",
       "  'no5': '1.0638'},\n",
       " {'date': '2019-01-01 02:00:00',\n",
       "  'no1': '1.0701',\n",
       "  'no2': '0.7203',\n",
       "  'no3': '0.3972',\n",
       "  'no4': '-0.0993',\n",
       "  'no5': '1.1648'}]"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lines[:3]  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "uuid": "2b2384ca-8927-49e1-8070-33ef0c21a1a9"
   },
   "outputs": [],
   "source": [
    "!rm -f $path*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### SQL Databases"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "uuid": "39c9650b-0430-4e66-b461-faecdb511537"
   },
   "outputs": [],
   "source": [
    "import sqlite3 as sq3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "uuid": "cc01fd41-a6c6-426b-b235-42c903ff6c00"
   },
   "outputs": [],
   "source": [
    "con = sq3.connect(path + 'numbs.db')  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "uuid": "9e163352-767b-4888-a286-9a79265bb19b"
   },
   "outputs": [],
   "source": [
    "query = 'CREATE TABLE numbs (Date date, No1 real, No2 real)'  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "uuid": "d97dad1a-10cc-43c0-a04a-a5da9b98396b"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<sqlite3.Cursor at 0x12a607440>"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "con.execute(query)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "uuid": "cc2e7d31-8239-48b0-b032-f11a514d9349"
   },
   "outputs": [],
   "source": [
    "con.commit()  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "q = con.execute  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('table',\n",
       "  'numbs',\n",
       "  'numbs',\n",
       "  2,\n",
       "  'CREATE TABLE numbs (Date date, No1 real, No2 real)')]"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q('SELECT * FROM sqlite_master').fetchall()  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "uuid": "6d76f99f-f6bb-4aad-b386-06946366bbe6"
   },
   "outputs": [],
   "source": [
    "import datetime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "uuid": "a37b7780-d824-4558-b12e-9e5dec6b3056"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<sqlite3.Cursor at 0x12a607040>"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "now = datetime.datetime.now()\n",
    "q('INSERT INTO numbs VALUES(?, ?, ?)', (now, 0.12, 7.3))  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "np.random.seed(100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "uuid": "5d882442-b6fb-4788-81b8-9f7814a352ae"
   },
   "outputs": [],
   "source": [
    "data = np.random.standard_normal((10000, 2)).round(4)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "uuid": "58b51e61-ed1a-4c5e-999a-0f55072e5d32"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 25.7 ms, sys: 2.77 ms, total: 28.5 ms\n",
      "Wall time: 28.1 ms\n"
     ]
    }
   ],
   "source": [
    "%%time \n",
    "for row in data:  \n",
    "    now = datetime.datetime.now()\n",
    "    q('INSERT INTO numbs VALUES(?, ?, ?)', (now, row[0], row[1]))\n",
    "con.commit()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "uuid": "667cbd3a-e001-4548-8679-10aec0d31354"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('2023-10-15 08:34:22.930842', 0.12, 7.3),\n",
       " ('2023-10-15 08:34:22.941673', -1.7498, 0.3427),\n",
       " ('2023-10-15 08:34:22.941995', 1.153, -0.2524),\n",
       " ('2023-10-15 08:34:22.942003', 0.9813, 0.5142)]"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q('SELECT * FROM numbs').fetchmany(4)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "uuid": "667cbd3a-e001-4548-8679-10aec0d31354"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('2023-10-15 08:34:22.941995', 1.153, -0.2524),\n",
       " ('2023-10-15 08:34:22.942003', 0.9813, 0.5142),\n",
       " ('2023-10-15 08:34:22.942017', 0.6727, -0.1044),\n",
       " ('2023-10-15 08:34:22.942025', 1.619, 1.5416)]"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q('SELECT * FROM numbs WHERE no1 > 0.5').fetchmany(4)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "uuid": "c9217058-4cb9-49b9-b81b-a4c370fce834"
   },
   "outputs": [],
   "source": [
    "pointer = q('SELECT * FROM numbs')  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "uuid": "7088d1c6-aed9-457a-a84a-58b1718ad164"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('2023-10-15 08:34:22.930842', 0.12, 7.3)\n",
      "('2023-10-15 08:34:22.941673', -1.7498, 0.3427)\n",
      "('2023-10-15 08:34:22.941995', 1.153, -0.2524)\n"
     ]
    }
   ],
   "source": [
    "for i in range(3):\n",
    "    print(pointer.fetchone())  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('2023-10-15 08:34:22.942003', 0.9813, 0.5142),\n",
       " ('2023-10-15 08:34:22.942006', 0.2212, -1.07),\n",
       " ('2023-10-15 08:34:22.942009', -0.1895, 0.255)]"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rows = pointer.fetchall()  \n",
    "rows[:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<sqlite3.Cursor at 0x12a606b40>"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q('DROP TABLE IF EXISTS numbs')  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q('SELECT * FROM sqlite_master').fetchall()  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "uuid": "3f80d448-2ff3-4e07-80ce-d8971f367a2c"
   },
   "outputs": [],
   "source": [
    "con.close()  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "uuid": "3f80d448-2ff3-4e07-80ce-d8971f367a2c"
   },
   "outputs": [],
   "source": [
    "!rm -f $path*  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Writing and Reading Numpy Arrays"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "uuid": "4e65636e-de0f-49d1-bd67-b63868fb3a3a"
   },
   "outputs": [],
   "source": [
    "dtimes = np.arange('2019-01-01 10:00:00', '2025-12-31 22:00:00',\n",
    "                  dtype='datetime64[m]')  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "uuid": "4e65636e-de0f-49d1-bd67-b63868fb3a3a"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3681360"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(dtimes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {
    "uuid": "d5d873f2-4ffa-4fad-a802-9c12a9e30046"
   },
   "outputs": [],
   "source": [
    "dty = np.dtype([('Date', 'datetime64[m]'),\n",
    "                ('No1', 'f'), ('No2', 'f')])  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {
    "uuid": "d5d873f2-4ffa-4fad-a802-9c12a9e30046"
   },
   "outputs": [],
   "source": [
    "data = np.zeros(len(dtimes), dtype=dty)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {
    "uuid": "d8cd7ec4-a323-44db-91ba-9a8a9edde1b4"
   },
   "outputs": [],
   "source": [
    "data['Date'] = dtimes  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {
    "uuid": "3f9e6dc3-23c8-46b2-b776-c5f73d22ce04"
   },
   "outputs": [],
   "source": [
    "a = np.random.standard_normal((len(dtimes), 2)).round(4)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {
    "uuid": "3f9e6dc3-23c8-46b2-b776-c5f73d22ce04"
   },
   "outputs": [],
   "source": [
    "data['No1'] = a[:, 0]  \n",
    "data['No2'] = a[:, 1]  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "58901760"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.nbytes  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {
    "uuid": "d783e0e3-0238-49f0-b3cf-655012d25ff3"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 699 µs, sys: 8.56 ms, total: 9.26 ms\n",
      "Wall time: 8.66 ms\n"
     ]
    }
   ],
   "source": [
    "%time np.save(path + 'array', data)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {
    "uuid": "329fb352-9724-4f9b-98e9-3d0d144c9cf9"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-rw-r--r--  1 yves  staff  58901888 Oct 15 08:34 /Users/yves/Temp/data/array.npy\n"
     ]
    }
   ],
   "source": [
    "ll $path*  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {
    "uuid": "b5f60285-80a3-4caa-b528-064b5302464b"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 1.47 ms, sys: 17.9 ms, total: 19.4 ms\n",
      "Wall time: 17.8 ms\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([('2019-01-01T10:00',  1.5131,  0.6973),\n",
       "       ('2019-01-01T10:01', -1.722 , -0.4815),\n",
       "       ('2019-01-01T10:02',  0.8251,  0.3019), ...,\n",
       "       ('2025-12-31T21:57',  1.372 ,  0.6446),\n",
       "       ('2025-12-31T21:58', -1.2542,  0.1612),\n",
       "       ('2025-12-31T21:59', -1.1997, -1.097 )],\n",
       "      dtype=[('Date', '<M8[m]'), ('No1', '<f4'), ('No2', '<f4')])"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%time np.load(path + 'array.npy')  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {
    "uuid": "d10836fb-aa11-4fb9-8c2c-24d46f48b46b"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 974 ms, sys: 159 ms, total: 1.13 s\n",
      "Wall time: 1.19 s\n"
     ]
    }
   ],
   "source": [
    "%time data = np.random.standard_normal((10000, 6000)).round(4)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "480000000"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.nbytes  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {
    "uuid": "2b48a768-2abb-46c1-9499-946e4e43f26e"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 522 µs, sys: 61.6 ms, total: 62.1 ms\n",
      "Wall time: 79.4 ms\n"
     ]
    }
   ],
   "source": [
    "%time np.save(path + 'array', data)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {
    "uuid": "c0de71b2-0d43-4752-82e4-982cc40fc47a"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-rw-r--r--  1 yves  staff  480000128 Oct 15 08:34 /Users/yves/Temp/data/array.npy\n"
     ]
    }
   ],
   "source": [
    "ll $path*   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {
    "uuid": "3bedfde2-d212-40e6-a043-379e416fcc08"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 1.25 ms, sys: 97.4 ms, total: 98.6 ms\n",
      "Wall time: 163 ms\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([[ 0.3066,  0.5951,  0.5826, ...,  1.6773,  0.4294, -0.2216],\n",
       "       [ 0.8769,  0.7292, -0.9557, ...,  0.5084,  0.9635, -0.4443],\n",
       "       [-1.2202, -2.5509, -0.0575, ..., -1.6128,  0.4662, -1.3645],\n",
       "       ...,\n",
       "       [-0.5598,  0.2393, -2.3716, ...,  1.7669,  0.2462,  1.035 ],\n",
       "       [ 0.273 ,  0.8216, -0.0749, ..., -0.0552, -0.8396,  0.3077],\n",
       "       [-0.6305,  0.8331,  1.3702, ...,  0.3493,  0.1981,  0.2037]])"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%time np.load(path + 'array.npy')  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {
    "uuid": "b5de422d-014e-4f1f-b80c-4c1333920a57"
   },
   "outputs": [],
   "source": [
    "!rm -f $path*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## I/O with pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {
    "uuid": "e0ba11e0-7bdf-4e1f-b8a2-0566cb5ab7a7"
   },
   "outputs": [],
   "source": [
    "data = np.random.standard_normal((1000000, 5)).round(4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0.4918,  1.3707,  0.137 ,  0.3981, -1.0059],\n",
       "       [ 0.4516,  1.4445,  0.0555, -0.0397,  0.44  ],\n",
       "       [ 0.1629, -0.8473, -0.8223, -0.4621, -0.5137]])"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[:3]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### SQL Database"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {
    "uuid": "366021ec-1265-4fef-ae96-b280c7f3cd2b"
   },
   "outputs": [],
   "source": [
    "filename = path + 'numbers'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {
    "uuid": "41eac653-cff4-4bab-b27a-18982f4b6159"
   },
   "outputs": [],
   "source": [
    "con = sq3.Connection(filename + '.db')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {
    "uuid": "296ae8af-8da3-4f6d-98bd-2816374d8526"
   },
   "outputs": [],
   "source": [
    "query = 'CREATE TABLE numbers (No1 real, No2 real,\\\n",
    "        No3 real, No4 real, No5 real)'  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [],
   "source": [
    "q = con.execute\n",
    "qm = con.executemany"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {
    "uuid": "8c1f7339-7383-4716-b1dc-d18bdd651bfe"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<sqlite3.Cursor at 0x12a605a40>"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q(query)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {
    "uuid": "c9bd1eba-510d-4b60-89bf-88dd90e96b4f"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 1.71 s, sys: 72.3 ms, total: 1.78 s\n",
      "Wall time: 1.79 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "qm('INSERT INTO numbers VALUES (?, ?, ?, ?, ?)', data)  \n",
    "con.commit()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {
    "uuid": "f2331de4-877b-48fe-aac1-fd823af82b24"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-rw-r--r--  1 yves  staff  52633600 Oct 15 08:34 /Users/yves/Temp/data/numbers.db\n"
     ]
    }
   ],
   "source": [
    "ll $path*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {
    "uuid": "36c34da0-f8d8-4bf5-8241-45266a118747"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[(0.4918, 1.3707, 0.137, 0.3981, -1.0059), (0.4516, 1.4445, 0.0555, -0.0397, 0.44), (0.1629, -0.8473, -0.8223, -0.4621, -0.5137)]\n",
      "CPU times: user 516 ms, sys: 39.8 ms, total: 556 ms\n",
      "Wall time: 556 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "temp = q('SELECT * FROM numbers').fetchall()  \n",
    "print(temp[:3])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {
    "uuid": "1ed09d3f-24a5-4936-b64c-a205182b5910"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 251 ms, sys: 26.3 ms, total: 278 ms\n",
      "Wall time: 278 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "query = 'SELECT * FROM numbers WHERE No1 > 0 AND No2 < 0'\n",
    "res = np.array(q(query).fetchall()).round(3)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {
    "uuid": "d3100151-5563-48ca-8ba6-cc9a623d03cc"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "res = res[::100]  \n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.plot(res[:, 0], res[:, 1], 'ro');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### From SQL to pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {
    "uuid": "d446ef85-a7d0-4aba-8b93-d2d60a1aee9b"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 1.61 s, sys: 129 ms, total: 1.74 s\n",
      "Wall time: 798 ms\n"
     ]
    }
   ],
   "source": [
    "%time data = pd.read_sql('SELECT * FROM numbers', con)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {
    "uuid": "052c40c0-6bb7-4084-9e84-da330dca43db"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>No1</th>\n",
       "      <th>No2</th>\n",
       "      <th>No3</th>\n",
       "      <th>No4</th>\n",
       "      <th>No5</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.4918</td>\n",
       "      <td>1.3707</td>\n",
       "      <td>0.1370</td>\n",
       "      <td>0.3981</td>\n",
       "      <td>-1.0059</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.4516</td>\n",
       "      <td>1.4445</td>\n",
       "      <td>0.0555</td>\n",
       "      <td>-0.0397</td>\n",
       "      <td>0.4400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.1629</td>\n",
       "      <td>-0.8473</td>\n",
       "      <td>-0.8223</td>\n",
       "      <td>-0.4621</td>\n",
       "      <td>-0.5137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.3064</td>\n",
       "      <td>0.9125</td>\n",
       "      <td>0.5142</td>\n",
       "      <td>-0.7868</td>\n",
       "      <td>-0.3398</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-0.1148</td>\n",
       "      <td>-1.5215</td>\n",
       "      <td>-0.7045</td>\n",
       "      <td>-1.0042</td>\n",
       "      <td>-0.0600</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      No1     No2     No3     No4     No5\n",
       "0  0.4918  1.3707  0.1370  0.3981 -1.0059\n",
       "1  0.4516  1.4445  0.0555 -0.0397  0.4400\n",
       "2  0.1629 -0.8473 -0.8223 -0.4621 -0.5137\n",
       "3  1.3064  0.9125  0.5142 -0.7868 -0.3398\n",
       "4 -0.1148 -1.5215 -0.7045 -1.0042 -0.0600"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {
    "uuid": "a5f5d023-dfbb-4b54-a622-38a48b3d00a1"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 8.26 ms, sys: 5.45 ms, total: 13.7 ms\n",
      "Wall time: 13.2 ms\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>No1</th>\n",
       "      <th>No2</th>\n",
       "      <th>No3</th>\n",
       "      <th>No4</th>\n",
       "      <th>No5</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.1629</td>\n",
       "      <td>-0.8473</td>\n",
       "      <td>-0.8223</td>\n",
       "      <td>-0.4621</td>\n",
       "      <td>-0.5137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.1893</td>\n",
       "      <td>-0.0207</td>\n",
       "      <td>-0.2104</td>\n",
       "      <td>0.9419</td>\n",
       "      <td>0.2551</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1.4784</td>\n",
       "      <td>-0.3333</td>\n",
       "      <td>-0.7050</td>\n",
       "      <td>0.3586</td>\n",
       "      <td>-0.3937</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.8092</td>\n",
       "      <td>-0.9899</td>\n",
       "      <td>1.0364</td>\n",
       "      <td>-1.0453</td>\n",
       "      <td>0.0579</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.9065</td>\n",
       "      <td>-0.7757</td>\n",
       "      <td>-0.9267</td>\n",
       "      <td>0.7797</td>\n",
       "      <td>0.0863</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       No1     No2     No3     No4     No5\n",
       "2   0.1629 -0.8473 -0.8223 -0.4621 -0.5137\n",
       "5   0.1893 -0.0207 -0.2104  0.9419  0.2551\n",
       "8   1.4784 -0.3333 -0.7050  0.3586 -0.3937\n",
       "10  0.8092 -0.9899  1.0364 -1.0453  0.0579\n",
       "11  0.9065 -0.7757 -0.9267  0.7797  0.0863"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%time data[(data['No1'] > 0) & (data['No2'] < 0)].head()  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {
    "uuid": "2aa6d1e0-e157-4d5b-8a43-3fc696679511"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 17.2 ms, sys: 4.01 ms, total: 21.2 ms\n",
      "Wall time: 14.4 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "q = '(No1 < -0.5 | No1 > 0.5) & (No2 < -1 | No2 > 1)'  \n",
    "res = data[['No1', 'No2']].query(q)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {
    "uuid": "d46cc119-c34b-4d3f-becd-f625c1a70f78"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 6))\n",
    "plt.plot(res['No1'], res['No2'], 'ro');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {
    "uuid": "7017f5f6-2a19-4d1e-b256-4936081ab91a"
   },
   "outputs": [],
   "source": [
    "h5s = pd.HDFStore(filename + '.h5s', 'w')  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {
    "uuid": "eec6ad05-c74e-49e9-bd35-965d56ba3bc9"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 13.2 ms, sys: 18.7 ms, total: 31.9 ms\n",
      "Wall time: 31.6 ms\n"
     ]
    }
   ],
   "source": [
    "%time h5s['data'] = data  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {
    "uuid": "69057178-872b-4080-8d36-3ea1d9b56b18"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<class 'pandas.io.pytables.HDFStore'>\n",
       "File path: /Users/yves/Temp/data/numbers.h5s"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "h5s  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {
    "uuid": "179c2cf9-9505-4e1a-b6fc-f71429bbfd6d"
   },
   "outputs": [],
   "source": [
    "h5s.close()  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {
    "uuid": "f13d24ff-afa4-453c-b098-ce986f0ec341"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 9.18 ms, sys: 13.1 ms, total: 22.3 ms\n",
      "Wall time: 22.1 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "h5s = pd.HDFStore(filename + '.h5s', 'r')  \n",
    "data_ = h5s['data']  \n",
    "h5s.close()  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 110,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_ is data  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "No1    True\n",
       "No2    True\n",
       "No3    True\n",
       "No4    True\n",
       "No5    True\n",
       "dtype: bool"
      ]
     },
     "execution_count": 111,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(data_ == data).all()  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {
    "uuid": "96b612da-9d26-498d-9b79-716d0bc9c5fa"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.allclose(data_, data)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {
    "uuid": "8d68e5ac-7434-4e1c-b5b8-0c6f03171826"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-rw-r--r--  1 yves  staff  52633600 Oct 15 08:34 /Users/yves/Temp/data/numbers.db\n",
      "-rw-r--r--  1 yves  staff  48007240 Oct 15 08:34 /Users/yves/Temp/data/numbers.h5s\n"
     ]
    }
   ],
   "source": [
    "ll $path*  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data as CSV File"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {
    "uuid": "7925d095-cbde-430b-b2ef-f0f143df15b8"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 2.12 s, sys: 58.7 ms, total: 2.18 s\n",
      "Wall time: 2.19 s\n"
     ]
    }
   ],
   "source": [
    "%time data.to_csv(filename + '.csv')  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "total 284632\n",
      "-rw-r--r--  1 yves  staff  43834157 Oct 15 08:34 numbers.csv\n",
      "-rw-r--r--  1 yves  staff  52633600 Oct 15 08:34 numbers.db\n",
      "-rw-r--r--  1 yves  staff  48007240 Oct 15 08:34 numbers.h5s\n"
     ]
    }
   ],
   "source": [
    "ll $path"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {
    "uuid": "074e493b-576f-4a3d-a9b5-cafd2045c75c"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 237 ms, sys: 37.3 ms, total: 274 ms\n",
      "Wall time: 288 ms\n"
     ]
    }
   ],
   "source": [
    "%time df = pd.read_csv(filename + '.csv')  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {
    "uuid": "074e493b-576f-4a3d-a9b5-cafd2045c75c"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[['No1', 'No2', 'No3', 'No4']].hist(bins=20, figsize=(10, 6));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data as Excel File"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {
    "uuid": "735350dc-e6af-4ee7-8f27-2505b3454682"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 8.59 s, sys: 360 ms, total: 8.95 s\n",
      "Wall time: 9.31 s\n"
     ]
    }
   ],
   "source": [
    "%time data[:100000].to_excel(filename + '.xlsx')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {
    "uuid": "0d2365b9-28b2-4bb5-8515-4c9ca628ec00"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 3.24 s, sys: 54.1 ms, total: 3.29 s\n",
      "Wall time: 3.43 s\n"
     ]
    }
   ],
   "source": [
    "%time df = pd.read_excel(filename + '.xlsx', 'Sheet1', index_col=0)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 100000 entries, 0 to 99999\n",
      "Data columns (total 5 columns):\n",
      " #   Column  Non-Null Count   Dtype  \n",
      "---  ------  --------------   -----  \n",
      " 0   No1     100000 non-null  float64\n",
      " 1   No2     100000 non-null  float64\n",
      " 2   No3     100000 non-null  float64\n",
      " 3   No4     100000 non-null  float64\n",
      " 4   No5     100000 non-null  float64\n",
      "dtypes: float64(5)\n",
      "memory usage: 4.6 MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {
    "uuid": "0d2365b9-28b2-4bb5-8515-4c9ca628ec00"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.cumsum().plot(figsize=(10, 6));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {
    "uuid": "0f0f0a19-994c-43ff-940f-9cd05b94a0cd"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-rw-r--r--  1 yves  staff  43834157 Oct 15 08:34 /Users/yves/Temp/data/numbers.csv\n",
      "-rw-r--r--  1 yves  staff  52633600 Oct 15 08:34 /Users/yves/Temp/data/numbers.db\n",
      "-rw-r--r--  1 yves  staff  48007240 Oct 15 08:34 /Users/yves/Temp/data/numbers.h5s\n",
      "-rw-r--r--  1 yves  staff   4012935 Oct 15 08:34 /Users/yves/Temp/data/numbers.xlsx\n"
     ]
    }
   ],
   "source": [
    "ll $path*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {
    "uuid": "638a2e35-0a12-41be-9743-c7f4f4afcb23"
   },
   "outputs": [],
   "source": [
    "rm -f $path*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Fast I/O with PyTables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {
    "uuid": "b671c317-5247-4a6b-94c9-0ee2850decba"
   },
   "outputs": [],
   "source": [
    "import tables as tb  \n",
    "import datetime as dt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Working with Tables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {
    "uuid": "4f7391d1-2f86-4913-af4d-2c603c970605"
   },
   "outputs": [],
   "source": [
    "filename = path + 'pytab.h5'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {
    "uuid": "4f7391d1-2f86-4913-af4d-2c603c970605"
   },
   "outputs": [],
   "source": [
    "h5 = tb.open_file(filename, 'w')  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {
    "uuid": "60a374d2-b78c-4473-b17a-69982fd27a4c"
   },
   "outputs": [],
   "source": [
    "row_des = {\n",
    "    'Date': tb.StringCol(26, pos=1),  \n",
    "    'No1': tb.IntCol(pos=2),  \n",
    "    'No2': tb.IntCol(pos=3),  \n",
    "    'No3': tb.Float64Col(pos=4),  \n",
    "    'No4': tb.Float64Col(pos=5)  \n",
    "    }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "metadata": {
    "uuid": "28c4dabe-bfbe-4a90-bd60-072c2e8f1aa1"
   },
   "outputs": [],
   "source": [
    "rows = 2000000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {
    "uuid": "027696b8-2e1b-489f-8cb6-c24c6c3702ee"
   },
   "outputs": [],
   "source": [
    "filters = tb.Filters(complevel=0)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {
    "uuid": "027696b8-2e1b-489f-8cb6-c24c6c3702ee"
   },
   "outputs": [],
   "source": [
    "tab = h5.create_table('/', 'ints_floats',  \n",
    "                      row_des,  \n",
    "                      title='Integers and Floats',  \n",
    "                      expectedrows=rows,  \n",
    "                      filters=filters)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tables.table.Table"
      ]
     },
     "execution_count": 131,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(tab)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {
    "uuid": "71ce6940-bde4-437f-9daa-f2f577f3cd7e"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "/ints_floats (Table(0,)) 'Integers and Floats'\n",
       "  description := {\n",
       "  \"Date\": StringCol(itemsize=26, shape=(), dflt=b'', pos=0),\n",
       "  \"No1\": Int32Col(shape=(), dflt=0, pos=1),\n",
       "  \"No2\": Int32Col(shape=(), dflt=0, pos=2),\n",
       "  \"No3\": Float64Col(shape=(), dflt=0.0, pos=3),\n",
       "  \"No4\": Float64Col(shape=(), dflt=0.0, pos=4)}\n",
       "  byteorder := 'little'\n",
       "  chunkshape := (2621,)"
      ]
     },
     "execution_count": 132,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tab"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {
    "uuid": "3830afd0-0a7b-439a-81b2-c81194deb7a5"
   },
   "outputs": [],
   "source": [
    "pointer = tab.row  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "metadata": {
    "uuid": "493096c9-7a8e-4342-b7c3-9390cbc03c6b"
   },
   "outputs": [],
   "source": [
    "ran_int = np.random.randint(0, 10000, size=(rows, 2))  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "metadata": {
    "uuid": "493096c9-7a8e-4342-b7c3-9390cbc03c6b"
   },
   "outputs": [],
   "source": [
    "ran_flo = np.random.standard_normal((rows, 2)).round(4)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {
    "uuid": "a15c64b5-17f2-4e11-b051-a6d68ba4bf7f"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 3.02 s, sys: 60.4 ms, total: 3.08 s\n",
      "Wall time: 3.1 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "for i in range(rows):\n",
    "    pointer['Date'] = dt.datetime.now()  \n",
    "    pointer['No1'] = ran_int[i, 0]  \n",
    "    pointer['No2'] = ran_int[i, 1]  \n",
    "    pointer['No3'] = ran_flo[i, 0]  \n",
    "    pointer['No4'] = ran_flo[i, 1]  \n",
    "    pointer.append()  \n",
    "tab.flush()  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "metadata": {
    "uuid": "0d0739a9-79a3-410a-abf0-20f6b8cef8c5"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "/ints_floats (Table(2000000,)) 'Integers and Floats'\n",
       "  description := {\n",
       "  \"Date\": StringCol(itemsize=26, shape=(), dflt=b'', pos=0),\n",
       "  \"No1\": Int32Col(shape=(), dflt=0, pos=1),\n",
       "  \"No2\": Int32Col(shape=(), dflt=0, pos=2),\n",
       "  \"No3\": Float64Col(shape=(), dflt=0.0, pos=3),\n",
       "  \"No4\": Float64Col(shape=(), dflt=0.0, pos=4)}\n",
       "  byteorder := 'little'\n",
       "  chunkshape := (2621,)"
      ]
     },
     "execution_count": 137,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tab  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {
    "uuid": "cff18aaa-9959-41a9-8f05-8ba42192368c"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-rw-r--r--  1 yves  staff  100156248 Oct 15 08:34 /Users/yves/Temp/data/pytab.h5\n"
     ]
    }
   ],
   "source": [
    "ll $path*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {
    "uuid": "2b81e6f0-86a1-429f-8d7c-ac4bbdcdd616"
   },
   "outputs": [],
   "source": [
    "dty = np.dtype([('Date', 'S26'), ('No1', '<i4'), ('No2', '<i4'),\n",
    "                                 ('No3', '<f8'), ('No4', '<f8')])  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {
    "uuid": "2b81e6f0-86a1-429f-8d7c-ac4bbdcdd616"
   },
   "outputs": [],
   "source": [
    "sarray = np.zeros(len(ran_int), dtype=dty)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {
    "uuid": "15ef6c1c-c760-4bdd-9e1b-fe46c108abf8"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([(b'', 0, 0, 0., 0.), (b'', 0, 0, 0., 0.), (b'', 0, 0, 0., 0.),\n",
       "       (b'', 0, 0, 0., 0.)],\n",
       "      dtype=[('Date', 'S26'), ('No1', '<i4'), ('No2', '<i4'), ('No3', '<f8'), ('No4', '<f8')])"
      ]
     },
     "execution_count": 141,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sarray[:4]  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {
    "uuid": "87071ae4-4ff2-402e-8746-037fee04b07c"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 29.3 ms, sys: 16.3 ms, total: 45.6 ms\n",
      "Wall time: 50.7 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "sarray['Date'] = dt.datetime.now()  \n",
    "sarray['No1'] = ran_int[:, 0]  \n",
    "sarray['No2'] = ran_int[:, 1]  \n",
    "sarray['No3'] = ran_flo[:, 0]  \n",
    "sarray['No4'] = ran_flo[:, 1]  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {
    "scrolled": true,
    "uuid": "992c3894-7eb7-4699-9e6b-2a6fb4e6eabf"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 8.21 ms, sys: 24.9 ms, total: 33.2 ms\n",
      "Wall time: 46.7 ms\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "/ints_floats_from_array (Table(2000000,)) 'Integers and Floats'\n",
       "  description := {\n",
       "  \"Date\": StringCol(itemsize=26, shape=(), dflt=b'', pos=0),\n",
       "  \"No1\": Int32Col(shape=(), dflt=0, pos=1),\n",
       "  \"No2\": Int32Col(shape=(), dflt=0, pos=2),\n",
       "  \"No3\": Float64Col(shape=(), dflt=0.0, pos=3),\n",
       "  \"No4\": Float64Col(shape=(), dflt=0.0, pos=4)}\n",
       "  byteorder := 'little'\n",
       "  chunkshape := (2621,)"
      ]
     },
     "execution_count": 143,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "h5.create_table('/', 'ints_floats_from_array', sarray,\n",
    "                      title='Integers and Floats',\n",
    "                      expectedrows=rows, filters=filters)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tables.file.File"
      ]
     },
     "execution_count": 144,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(h5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {
    "uuid": "a7616365-19cf-4cbb-a6a0-01c3b88cb457"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "File(filename=/Users/yves/Temp/data/pytab.h5, title='', mode='w', root_uep='/', filters=Filters(complevel=0, shuffle=False, bitshuffle=False, fletcher32=False, least_significant_digit=None))\n",
       "/ (RootGroup) ''\n",
       "/ints_floats (Table(2000000,)) 'Integers and Floats'\n",
       "  description := {\n",
       "  \"Date\": StringCol(itemsize=26, shape=(), dflt=b'', pos=0),\n",
       "  \"No1\": Int32Col(shape=(), dflt=0, pos=1),\n",
       "  \"No2\": Int32Col(shape=(), dflt=0, pos=2),\n",
       "  \"No3\": Float64Col(shape=(), dflt=0.0, pos=3),\n",
       "  \"No4\": Float64Col(shape=(), dflt=0.0, pos=4)}\n",
       "  byteorder := 'little'\n",
       "  chunkshape := (2621,)\n",
       "/ints_floats_from_array (Table(2000000,)) 'Integers and Floats'\n",
       "  description := {\n",
       "  \"Date\": StringCol(itemsize=26, shape=(), dflt=b'', pos=0),\n",
       "  \"No1\": Int32Col(shape=(), dflt=0, pos=1),\n",
       "  \"No2\": Int32Col(shape=(), dflt=0, pos=2),\n",
       "  \"No3\": Float64Col(shape=(), dflt=0.0, pos=3),\n",
       "  \"No4\": Float64Col(shape=(), dflt=0.0, pos=4)}\n",
       "  byteorder := 'little'\n",
       "  chunkshape := (2621,)"
      ]
     },
     "execution_count": 145,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "h5  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {
    "uuid": "f498bb1c-ef46-4ee9-956d-21f292687323"
   },
   "outputs": [],
   "source": [
    "h5.remove_node('/', 'ints_floats_from_array')  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {
    "uuid": "e99634bc-effd-43ee-ac2e-4b66b925433b"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([(b'2023-10-15 08:34:46.431496', 8576, 5991, -0.0528, 0.2468),\n",
       "       (b'2023-10-15 08:34:46.432546', 2990, 9310, -0.0261, 0.3932),\n",
       "       (b'2023-10-15 08:34:46.432551', 4400, 4823,  0.9133, 0.2579)],\n",
       "      dtype=[('Date', 'S26'), ('No1', '<i4'), ('No2', '<i4'), ('No3', '<f8'), ('No4', '<f8')])"
      ]
     },
     "execution_count": 147,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tab[:3]  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "metadata": {
    "uuid": "d84a41bd-36d3-4e11-8a4d-44440551a493"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.2468,  0.3932,  0.2579, -0.5582])"
      ]
     },
     "execution_count": 148,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tab[:4]['No4']  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {
    "uuid": "f7616601-4e98-42cc-9935-c855877d178c"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 10.6 ms, sys: 35.1 ms, total: 45.7 ms\n",
      "Wall time: 55.3 ms\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "88.8542999999997"
      ]
     },
     "execution_count": 149,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%time np.sum(tab[:]['No3'])  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "metadata": {
    "uuid": "9061ed32-44db-4c13-a44a-92b313b4af40"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 8.96 ms, sys: 20.7 ms, total: 29.6 ms\n",
      "Wall time: 28.5 ms\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "133349920.3689251"
      ]
     },
     "execution_count": 150,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%time np.sum(np.sqrt(tab[:]['No1']))  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "metadata": {
    "uuid": "558b4627-15f8-4a8f-8d5a-fc7213ee074e"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 45.8 ms, sys: 26.1 ms, total: 71.9 ms\n",
      "Wall time: 74.1 ms\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%time\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.hist(tab[:]['No3'], bins=30);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "metadata": {
    "uuid": "62ea755e-493b-4230-96ad-0ce7a0a33acc"
   },
   "outputs": [],
   "source": [
    "query = '((No3 < -0.5) | (No3 > 0.5)) & ((No4 < -1) | (No4 > 1))'  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "metadata": {
    "uuid": "62ea755e-493b-4230-96ad-0ce7a0a33acc"
   },
   "outputs": [],
   "source": [
    "iterator = tab.where(query)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "metadata": {
    "uuid": "62ea755e-493b-4230-96ad-0ce7a0a33acc"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 443 ms, sys: 99 ms, total: 542 ms\n",
      "Wall time: 95.9 ms\n"
     ]
    }
   ],
   "source": [
    "%time res = [(row['No3'], row['No4']) for row in iterator]  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "metadata": {
    "uuid": "62ea755e-493b-4230-96ad-0ce7a0a33acc"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.7694, 1.4866],\n",
       "       [0.9201, 1.3346],\n",
       "       [1.4701, 1.8776]])"
      ]
     },
     "execution_count": 155,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res = np.array(res)  \n",
    "res[:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {
    "uuid": "705d91ca-dc94-4db1-84d7-164fb5f5f1af"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 6))\n",
    "plt.plot(res.T[0], res.T[1], 'ro');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "metadata": {
    "uuid": "a9e8e16c-9af5-48dc-bf5c-39b353f5c09b"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Max              5.224\n",
      "Ave              0.000\n",
      "Min             -5.649\n",
      "Std              1.000\n",
      "CPU times: user 82.1 ms, sys: 17.2 ms, total: 99.3 ms\n",
      "Wall time: 40.3 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "values = tab[:]['No3']\n",
    "print('Max %18.3f' % values.max())\n",
    "print('Ave %18.3f' % values.mean())\n",
    "print('Min %18.3f' % values.min())\n",
    "print('Std %18.3f' % values.std())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {
    "uuid": "6cfb0992-c393-45b0-999b-b242ea9c1ce6"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 29.8 ms, sys: 18.7 ms, total: 48.5 ms\n",
      "Wall time: 29.9 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "res = [(row['No1'], row['No2']) for row in\n",
    "        tab.where('((No1 > 9800) | (No1 < 200)) \\\n",
    "                & ((No2 > 4500) & (No2 < 5500))')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "metadata": {
    "uuid": "6cfb0992-c393-45b0-999b-b242ea9c1ce6"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(91, 4870)\n",
      "(9803, 5026)\n",
      "(9846, 4859)\n",
      "(9823, 5069)\n"
     ]
    }
   ],
   "source": [
    "for r in res[:4]:\n",
    "    print(r)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {
    "uuid": "399c76db-4f79-4264-b25f-50eab32303e0"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 16.3 ms, sys: 16.6 ms, total: 33 ms\n",
      "Wall time: 25 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "res = [(row['No1'], row['No2']) for row in\n",
    "        tab.where('(No1 == 1234) & (No2 > 9776)')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "metadata": {
    "uuid": "399c76db-4f79-4264-b25f-50eab32303e0"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1234, 9841)\n",
      "(1234, 9821)\n",
      "(1234, 9867)\n",
      "(1234, 9987)\n",
      "(1234, 9849)\n",
      "(1234, 9800)\n"
     ]
    }
   ],
   "source": [
    "for r in res:\n",
    "    print(r)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Working with Compressed Tables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {
    "uuid": "4e6ac124-2500-47c5-9478-2eaaba25ea00"
   },
   "outputs": [],
   "source": [
    "filename = path + 'pytabc.h5'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "metadata": {
    "uuid": "4e6ac124-2500-47c5-9478-2eaaba25ea00"
   },
   "outputs": [],
   "source": [
    "h5c = tb.open_file(filename, 'w') "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {
    "uuid": "830338b0-ec10-4f95-8058-62b1858b46b7"
   },
   "outputs": [],
   "source": [
    "filters = tb.Filters(complevel=5,  \n",
    "                     complib='blosc')  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {
    "uuid": "d11f1cdc-c54a-49f3-992d-b76f7cad5a4a"
   },
   "outputs": [],
   "source": [
    "tabc = h5c.create_table('/', 'ints_floats', sarray,\n",
    "                        title='Integers and Floats',\n",
    "                        expectedrows=rows, filters=filters)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {
    "uuid": "62ea755e-493b-4230-96ad-0ce7a0a33acc"
   },
   "outputs": [],
   "source": [
    "query = '((No3 < -0.5) | (No3 > 0.5)) & ((No4 < -1) | (No4 > 1))'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {
    "uuid": "62ea755e-493b-4230-96ad-0ce7a0a33acc"
   },
   "outputs": [],
   "source": [
    "iteratorc = tabc.where(query)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "metadata": {
    "uuid": "62ea755e-493b-4230-96ad-0ce7a0a33acc"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 79.6 ms, sys: 27.3 ms, total: 107 ms\n",
      "Wall time: 87.4 ms\n"
     ]
    }
   ],
   "source": [
    "%time res = [(row['No3'], row['No4']) for row in iteratorc]  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.7694, 1.4866],\n",
       "       [0.9201, 1.3346],\n",
       "       [1.4701, 1.8776]])"
      ]
     },
     "execution_count": 169,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res = np.array(res)\n",
    "res[:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "metadata": {
    "uuid": "f4e1df40-c747-49a2-815c-f1cbd33f621d"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 5.45 ms, sys: 19.8 ms, total: 25.3 ms\n",
      "Wall time: 28.5 ms\n"
     ]
    }
   ],
   "source": [
    "%time arr_non = tab.read()  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "metadata": {
    "uuid": "f4e1df40-c747-49a2-815c-f1cbd33f621d"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "100122200"
      ]
     },
     "execution_count": 171,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tab.size_on_disk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "100000000"
      ]
     },
     "execution_count": 172,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "arr_non.nbytes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {
    "uuid": "f7428798-5946-49be-88b1-d67d26a41e70"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 6.81 ms, sys: 29.1 ms, total: 35.9 ms\n",
      "Wall time: 54.6 ms\n"
     ]
    }
   ],
   "source": [
    "%time arr_com = tabc.read()  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {
    "uuid": "f4e1df40-c747-49a2-815c-f1cbd33f621d"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "99995412"
      ]
     },
     "execution_count": 174,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tabc.size_on_disk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "100000000"
      ]
     },
     "execution_count": 175,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "arr_com.nbytes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {
    "uuid": "e21f417f-f123-41b5-b26b-ecebbbaa5c85"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-rw-r--r--  1 yves  staff  200312336 Oct 15 08:34 /Users/yves/Temp/data/pytab.h5\n",
      "-rw-r--r--  1 yves  staff  100030708 Oct 15 08:34 /Users/yves/Temp/data/pytabc.h5\n"
     ]
    }
   ],
   "source": [
    "ll $path*  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "metadata": {
    "uuid": "ea7dd80f-44d8-4cd9-a16f-308a302dd460"
   },
   "outputs": [],
   "source": [
    "h5c.close()  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "uuid": "ee67fc74-5820-4037-b8d9-281c74435160"
   },
   "source": [
    "### Working with Arrays"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "metadata": {
    "uuid": "ee67fc74-5820-4037-b8d9-281c74435160"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 1.26 ms, sys: 11.7 ms, total: 12.9 ms\n",
      "Wall time: 44.5 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "arr_int = h5.create_array('/', 'integers', ran_int)  \n",
    "arr_flo = h5.create_array('/', 'floats', ran_flo)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "metadata": {
    "uuid": "c91c089b-4727-4928-8069-2f74ab1f2c61"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "File(filename=/Users/yves/Temp/data/pytab.h5, title='', mode='w', root_uep='/', filters=Filters(complevel=0, shuffle=False, bitshuffle=False, fletcher32=False, least_significant_digit=None))\n",
       "/ (RootGroup) ''\n",
       "/floats (Array(2000000, 2)) ''\n",
       "  atom := Float64Atom(shape=(), dflt=0.0)\n",
       "  maindim := 0\n",
       "  flavor := 'numpy'\n",
       "  byteorder := 'little'\n",
       "  chunkshape := None\n",
       "/integers (Array(2000000, 2)) ''\n",
       "  atom := Int64Atom(shape=(), dflt=0)\n",
       "  maindim := 0\n",
       "  flavor := 'numpy'\n",
       "  byteorder := 'little'\n",
       "  chunkshape := None\n",
       "/ints_floats (Table(2000000,)) 'Integers and Floats'\n",
       "  description := {\n",
       "  \"Date\": StringCol(itemsize=26, shape=(), dflt=b'', pos=0),\n",
       "  \"No1\": Int32Col(shape=(), dflt=0, pos=1),\n",
       "  \"No2\": Int32Col(shape=(), dflt=0, pos=2),\n",
       "  \"No3\": Float64Col(shape=(), dflt=0.0, pos=3),\n",
       "  \"No4\": Float64Col(shape=(), dflt=0.0, pos=4)}\n",
       "  byteorder := 'little'\n",
       "  chunkshape := (2621,)"
      ]
     },
     "execution_count": 179,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "h5  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "metadata": {
    "uuid": "5bf3d20c-0dd1-447f-b7ca-34adb0e9a2c6"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-rw-r--r--  1 yves  staff  262344490 Oct 15 08:34 /Users/yves/Temp/data/pytab.h5\n",
      "-rw-r--r--  1 yves  staff  100030708 Oct 15 08:34 /Users/yves/Temp/data/pytabc.h5\n"
     ]
    }
   ],
   "source": [
    "ll $path*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "metadata": {
    "uuid": "3dfffbc8-ab8e-4c6e-9e18-316d220e51a0"
   },
   "outputs": [],
   "source": [
    "h5.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "metadata": {
    "uuid": "2a157cb2-dcc1-44fe-b4da-658bbe2b6ebb"
   },
   "outputs": [],
   "source": [
    "!rm -f $path*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Out-of-Memory Computations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "metadata": {
    "uuid": "e241b3b2-bfe1-45b4-9e85-0b39586ca42a"
   },
   "outputs": [],
   "source": [
    "filename = path + 'earray.h5'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "metadata": {
    "uuid": "e241b3b2-bfe1-45b4-9e85-0b39586ca42a"
   },
   "outputs": [],
   "source": [
    "h5 = tb.open_file(filename, 'w') "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "metadata": {
    "uuid": "dd0e24b0-d0cc-4cb0-90e0-7c6445dcb1d2"
   },
   "outputs": [],
   "source": [
    "n = 500  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 186,
   "metadata": {
    "uuid": "dd0e24b0-d0cc-4cb0-90e0-7c6445dcb1d2"
   },
   "outputs": [],
   "source": [
    "ear = h5.create_earray('/', 'ear',  \n",
    "                      atom=tb.Float64Atom(),  \n",
    "                      shape=(0, n))  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tables.earray.EArray"
      ]
     },
     "execution_count": 187,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(ear)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 188,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-1.25983231,  1.11420699,  0.1667485 ,  0.7345676 ],\n",
       "       [-0.13785424,  1.22232417,  1.36303097,  0.13521042],\n",
       "       [ 1.45487119, -1.47784078,  0.15027672,  0.86755989],\n",
       "       [-0.63519366,  0.1516327 , -0.64939447, -0.45010975]])"
      ]
     },
     "execution_count": 188,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rand = np.random.standard_normal((n, n))  \n",
    "rand[:4, :4]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 189,
   "metadata": {
    "uuid": "4dabef84-39ca-4dd4-a8ab-edc65d340965"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 141 ms, sys: 465 ms, total: 606 ms\n",
      "Wall time: 797 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "for _ in range(750):\n",
    "    ear.append(rand)  \n",
    "ear.flush()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 190,
   "metadata": {
    "uuid": "4dd0218f-b9ca-4ee5-8a1f-af071e346c55"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "/ear (EArray(375000, 500)) ''\n",
       "  atom := Float64Atom(shape=(), dflt=0.0)\n",
       "  maindim := 0\n",
       "  flavor := 'numpy'\n",
       "  byteorder := 'little'\n",
       "  chunkshape := (16, 500)"
      ]
     },
     "execution_count": 190,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ear"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 191,
   "metadata": {
    "uuid": "58694407-5d44-400d-99a1-252ea1595514"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1500032000"
      ]
     },
     "execution_count": 191,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ear.size_on_disk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 192,
   "metadata": {
    "uuid": "f29bef2e-37fb-4f47-83fd-ef09041f2f77"
   },
   "outputs": [],
   "source": [
    "out = h5.create_earray('/', 'out',\n",
    "                      atom=tb.Float64Atom(),\n",
    "                      shape=(0, n))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 193,
   "metadata": {
    "uuid": "f29bef2e-37fb-4f47-83fd-ef09041f2f77"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 193,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "out.size_on_disk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 194,
   "metadata": {
    "uuid": "aedc7c36-5839-4df5-8391-f0620b2c1381"
   },
   "outputs": [],
   "source": [
    "expr = tb.Expr('3 * sin(ear) + sqrt(abs(ear))')  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 195,
   "metadata": {
    "uuid": "aedc7c36-5839-4df5-8391-f0620b2c1381"
   },
   "outputs": [],
   "source": [
    "expr.set_output(out, append_mode=True)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 196,
   "metadata": {
    "uuid": "79542d3f-60fe-4303-abb8-2a21ce9512f2"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 2.27 s, sys: 932 ms, total: 3.2 s\n",
      "Wall time: 1.65 s\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "/out (EArray(375000, 500)) ''\n",
       "  atom := Float64Atom(shape=(), dflt=0.0)\n",
       "  maindim := 0\n",
       "  flavor := 'numpy'\n",
       "  byteorder := 'little'\n",
       "  chunkshape := (16, 500)"
      ]
     },
     "execution_count": 196,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%time expr.eval()  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 197,
   "metadata": {
    "uuid": "79542d3f-60fe-4303-abb8-2a21ce9512f2"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1500032000"
      ]
     },
     "execution_count": 197,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "out.size_on_disk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 198,
   "metadata": {
    "uuid": "19d61e69-3488-4556-8d2b-cc06edb9c39e"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-1.73369462,  3.74824436,  0.90627898,  2.86786818,  1.75424957,\n",
       "       -0.91108973, -1.68313885,  1.29073295, -1.68665599, -1.71345309])"
      ]
     },
     "execution_count": 198,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "out[0, :10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 199,
   "metadata": {
    "uuid": "2409ddc9-2963-4599-9d8c-a3abc1e010d3"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 116 ms, sys: 531 ms, total: 647 ms\n",
      "Wall time: 810 ms\n"
     ]
    }
   ],
   "source": [
    "%time out_ = out.read()  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 200,
   "metadata": {
    "uuid": "2409ddc9-2963-4599-9d8c-a3abc1e010d3"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-1.73369462,  3.74824436,  0.90627898,  2.86786818,  1.75424957,\n",
       "       -0.91108973, -1.68313885,  1.29073295, -1.68665599, -1.71345309])"
      ]
     },
     "execution_count": 200,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "out_[0, :10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 201,
   "metadata": {
    "uuid": "65d5272f-66d9-4fdd-a16a-ae900f2842c4"
   },
   "outputs": [],
   "source": [
    "import numexpr as ne  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 202,
   "metadata": {
    "uuid": "65d5272f-66d9-4fdd-a16a-ae900f2842c4"
   },
   "outputs": [],
   "source": [
    "expr = '3 * sin(out_) + sqrt(abs(out_))'  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 203,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8"
      ]
     },
     "execution_count": 203,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ne.set_num_threads(1)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 204,
   "metadata": {
    "uuid": "d58a70be-dc0f-444f-895d-9115864059c8"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 1.76 s, sys: 602 ms, total: 2.36 s\n",
      "Wall time: 2.43 s\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([-1.64358578,  0.22567882,  3.31363043,  2.50443549,  4.27413965,\n",
       "       -1.41600606, -1.68373023,  4.01921805, -1.68117412, -1.66053597])"
      ]
     },
     "execution_count": 204,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%time ne.evaluate(expr)[0, :10]  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 205,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 205,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ne.set_num_threads(4)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 206,
   "metadata": {
    "uuid": "d58a70be-dc0f-444f-895d-9115864059c8"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 1.97 s, sys: 348 ms, total: 2.32 s\n",
      "Wall time: 671 ms\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([-1.64358578,  0.22567882,  3.31363043,  2.50443549,  4.27413965,\n",
       "       -1.41600606, -1.68373023,  4.01921805, -1.68117412, -1.66053597])"
      ]
     },
     "execution_count": 206,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%time ne.evaluate(expr)[0, :10]  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 207,
   "metadata": {
    "uuid": "d0c3ef43-f285-4dc1-b0ab-af206e6b3dd6"
   },
   "outputs": [],
   "source": [
    "h5.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 208,
   "metadata": {
    "uuid": "4343a20a-8132-4fbf-9360-3a627da7d0cf"
   },
   "outputs": [],
   "source": [
    "!rm -f $path*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## TsTables"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Sample Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 209,
   "metadata": {},
   "outputs": [],
   "source": [
    "no = 5000000  \n",
    "co = 3  \n",
    "interval = 1. / (12 * 30 * 24 * 60)  \n",
    "vol = 0.2  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 210,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 335 ms, sys: 52.7 ms, total: 388 ms\n",
      "Wall time: 386 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "rn = np.random.standard_normal((no, co))  \n",
    "rn[0] = 0.0  \n",
    "paths = 100 * np.exp(np.cumsum(-0.5 * vol ** 2 * interval +\n",
    "        vol * np.sqrt(interval) * rn, axis=0))  \n",
    "paths[0] = 100  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 211,
   "metadata": {},
   "outputs": [],
   "source": [
    "dr = pd.date_range('2019-1-1', periods=no, freq='1s')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 212,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2019-02-27 20:53:14', '2019-02-27 20:53:15',\n",
       "               '2019-02-27 20:53:16', '2019-02-27 20:53:17',\n",
       "               '2019-02-27 20:53:18', '2019-02-27 20:53:19'],\n",
       "              dtype='datetime64[ns]', freq='S')"
      ]
     },
     "execution_count": 212,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dr[-6:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 213,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.DataFrame(paths, index=dr, columns=['ts1', 'ts2', 'ts3'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 214,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "DatetimeIndex: 5000000 entries, 2019-01-01 00:00:00 to 2019-02-27 20:53:19\n",
      "Freq: S\n",
      "Data columns (total 3 columns):\n",
      " #   Column  Dtype  \n",
      "---  ------  -----  \n",
      " 0   ts1     float64\n",
      " 1   ts2     float64\n",
      " 2   ts3     float64\n",
      "dtypes: float64(3)\n",
      "memory usage: 152.6 MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 215,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ts1</th>\n",
       "      <th>ts2</th>\n",
       "      <th>ts3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-01-01 00:00:00</th>\n",
       "      <td>100.000000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-01 00:00:01</th>\n",
       "      <td>100.018443</td>\n",
       "      <td>99.966644</td>\n",
       "      <td>99.998255</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-01 00:00:02</th>\n",
       "      <td>100.069023</td>\n",
       "      <td>100.004420</td>\n",
       "      <td>99.986646</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-01 00:00:03</th>\n",
       "      <td>100.086757</td>\n",
       "      <td>100.000246</td>\n",
       "      <td>99.992042</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-01 00:00:04</th>\n",
       "      <td>100.105448</td>\n",
       "      <td>100.036033</td>\n",
       "      <td>99.950618</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            ts1         ts2         ts3\n",
       "2019-01-01 00:00:00  100.000000  100.000000  100.000000\n",
       "2019-01-01 00:00:01  100.018443   99.966644   99.998255\n",
       "2019-01-01 00:00:02  100.069023  100.004420   99.986646\n",
       "2019-01-01 00:00:03  100.086757  100.000246   99.992042\n",
       "2019-01-01 00:00:04  100.105448  100.036033   99.950618"
      ]
     },
     "execution_count": 215,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 216,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[::100000].plot(figsize=(10, 6));\n",
    "# plt.savefig('../../images/ch09/io_07.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data Storage (with `tstables`)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<b style=\"color: red;\">Install the package as follows:</b>\n",
    "\n",
    "    pip install git+https://github.com/yhilpisch/tstables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 217,
   "metadata": {},
   "outputs": [],
   "source": [
    "import tstables as tstab"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 218,
   "metadata": {},
   "outputs": [],
   "source": [
    "class ts_desc(tb.IsDescription):\n",
    "    timestamp = tb.Int64Col(pos=0)  \n",
    "    ts1 = tb.Float64Col(pos=1)  \n",
    "    ts2 = tb.Float64Col(pos=2)  \n",
    "    ts3 = tb.Float64Col(pos=3)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 219,
   "metadata": {},
   "outputs": [],
   "source": [
    "h5 = tb.open_file(path + 'tstab.h5', 'w')  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 220,
   "metadata": {},
   "outputs": [],
   "source": [
    "ts = h5.create_ts('/', 'ts', ts_desc)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 221,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 184 ms, sys: 117 ms, total: 300 ms\n",
      "Wall time: 321 ms\n"
     ]
    }
   ],
   "source": [
    "%time ts.append(df)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 222,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tstables.tstable.TsTable"
      ]
     },
     "execution_count": 222,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(ts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 223,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "total 253616\n",
      "-rw-r--r--  1 501  20  129850400 Oct 15 08:35 tstab.h5\n"
     ]
    }
   ],
   "source": [
    "ls -n $path"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 224,
   "metadata": {},
   "outputs": [],
   "source": [
    "read_start_dt = dt.datetime(2019, 2, 1, 0, 0)  \n",
    "read_end_dt = dt.datetime(2019, 2, 5, 23, 59)  #<2>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 225,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 27.7 ms, sys: 26.6 ms, total: 54.3 ms\n",
      "Wall time: 55.9 ms\n"
     ]
    }
   ],
   "source": [
    "%time rows = ts.read_range(read_start_dt, read_end_dt)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 226,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "DatetimeIndex: 431941 entries, 2019-02-01 00:00:00 to 2019-02-05 23:59:00\n",
      "Data columns (total 3 columns):\n",
      " #   Column  Non-Null Count   Dtype  \n",
      "---  ------  --------------   -----  \n",
      " 0   ts1     431941 non-null  float64\n",
      " 1   ts2     431941 non-null  float64\n",
      " 2   ts3     431941 non-null  float64\n",
      "dtypes: float64(3)\n",
      "memory usage: 13.2 MB\n"
     ]
    }
   ],
   "source": [
    "rows.info()  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 227,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ts1</th>\n",
       "      <th>ts2</th>\n",
       "      <th>ts3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-02-01 00:00:00</th>\n",
       "      <td>52.063640</td>\n",
       "      <td>40.474580</td>\n",
       "      <td>217.324713</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-02-01 00:00:01</th>\n",
       "      <td>52.087455</td>\n",
       "      <td>40.471911</td>\n",
       "      <td>217.250070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-02-01 00:00:02</th>\n",
       "      <td>52.084808</td>\n",
       "      <td>40.458013</td>\n",
       "      <td>217.228712</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-02-01 00:00:03</th>\n",
       "      <td>52.073536</td>\n",
       "      <td>40.451408</td>\n",
       "      <td>217.302912</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-02-01 00:00:04</th>\n",
       "      <td>52.056133</td>\n",
       "      <td>40.450951</td>\n",
       "      <td>217.207481</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           ts1        ts2         ts3\n",
       "2019-02-01 00:00:00  52.063640  40.474580  217.324713\n",
       "2019-02-01 00:00:01  52.087455  40.471911  217.250070\n",
       "2019-02-01 00:00:02  52.084808  40.458013  217.228712\n",
       "2019-02-01 00:00:03  52.073536  40.451408  217.302912\n",
       "2019-02-01 00:00:04  52.056133  40.450951  217.207481"
      ]
     },
     "execution_count": 227,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rows.head()  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 228,
   "metadata": {},
   "outputs": [],
   "source": [
    "h5.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 229,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "(rows[::500] / rows.iloc[0]).plot(figsize=(10, 6));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 230,
   "metadata": {},
   "outputs": [],
   "source": [
    "import random"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 231,
   "metadata": {},
   "outputs": [],
   "source": [
    "h5 = tb.open_file(path + 'tstab.h5', 'r')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 232,
   "metadata": {},
   "outputs": [],
   "source": [
    "ts = h5.root.ts._f_get_timeseries()  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 233,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 1.35 s, sys: 454 ms, total: 1.8 s\n",
      "Wall time: 1.99 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "for _ in range(100):  \n",
    "    d = random.randint(1, 24)  \n",
    "    read_start_dt = dt.datetime(2019, 2, d, 0, 0, 0)\n",
    "    read_end_dt = dt.datetime(2019, 2, d + 3, 23, 59, 59)\n",
    "    rows = ts.read_range(read_start_dt, read_end_dt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 234,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "DatetimeIndex: 345600 entries, 2019-02-08 00:00:00 to 2019-02-11 23:59:59\n",
      "Data columns (total 3 columns):\n",
      " #   Column  Non-Null Count   Dtype  \n",
      "---  ------  --------------   -----  \n",
      " 0   ts1     345600 non-null  float64\n",
      " 1   ts2     345600 non-null  float64\n",
      " 2   ts3     345600 non-null  float64\n",
      "dtypes: float64(3)\n",
      "memory usage: 10.5 MB\n"
     ]
    }
   ],
   "source": [
    "rows.info()  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 235,
   "metadata": {},
   "outputs": [],
   "source": [
    "!rm $path/tstab.h5"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"http://hilpisch.com/tpq_logo.png\" alt=\"The Python Quants\" width=\"35%\" align=\"right\" border=\"0\"><br>\n",
    "\n",
    "<a href=\"http://tpq.io\" target=\"_blank\">http://tpq.io</a> | <a href=\"http://twitter.com/dyjh\" target=\"_blank\">@dyjh</a> | <a href=\"mailto:training@tpq.io\">training@tpq.io</a>"
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
